Tag Archives: W Edwards Deming

Deconstructing Deming VI – Institute training on the job

Posted on by
Reply

6. Institute training on the job.

W Edwards Deming Point 6 of Deming’s 14 Points. I think it was this point that made me realise that everybody projects their own anxieties onto Deming’s writings and finds what they want to find there.

Deming elaborates this point further in Out of the Crisis and several distinct positions emerge. I identify nine. In many ways, the slogan Institute training on the job is no very good description of what Deming was seeking to communicate. Not everything sits well under this heading.

“Training”, along with its sagacious uncle, “education” is one of those things that every one can be in favour of. The systems by which the accumulated knowledge of humanity are communicated, criticised and developed are the foundations of civilisation. But like all accepted truths some scrutiny repays the time and effort. Here are the nine topics I identified in Out of the Crisis.

1. People don’t spend enough on training because the benefits do not show on the balance sheet

This was one of Deming’s targets behind his sixth point. It reiterates a common theme of his. It goes back to the criticisms of Hayes and Abernathy that managers were incapable of understanding their own business. Without such understanding, a manager would lack a narrative to envision the future material rewards of current spending. Cash movements showed on the profit and loss account. The spending became merely an overhead to be attacked so as to enhance the current picture of performance projected by the accounts, the visible figures.

I have considered Hayes and Abernathy’s analysis elsewhere. Whatever the conditions of the early 1980s in the US, I think today’s global marketplace is a very different arena. Organisations vie to invest in their people, as this recent Forbes article shows (though the author can’t spell “bellwether”). True, the article confirms that development spending falls in a recession but cash flow and the availability of working capital are real constraints on a business and have to be managed. Once optimism returns, training spend takes off.

But as US satirist P J O’Rourke observed:

Getting people to give vast amounts of money when there’s no firm idea what that money will do is like throwing maidens down a well. It’s an appeal to magic. And the results are likely to be as stupid and disappointing as the results of magic usually are.

The tragedy of so many corporations is that training budgets are set and value measured on how much money is spent, in the idealistic but sentimental belief that training is an inherent good and that rewards will inevitably flow to those who have faith.

The reality is that it is only within a system of rigorous goal deployment that local training objectives can be identified so as to serve corporate strategy. Only then can training be designed to serve those objectives and only then can training’s value be measured.

2. Root Cause Analysis

The other arena in which the word “training” is guaranteed to turn up is during Root Cause Analysis. It is a moral certainty that somebody will volunteer it somewhere on the Ishikawa diagram. “To stop this happening again, let’s repeat the training.”

Yet, failure of training can never be the root cause of a problem or defect. Such an assertion yields too readily to the question Why did lack of training cause the failure?. The Why? question exposes that there was something the training was supposed to do. It could be that the root cause is readily identified and training put in place as a solution. But, the question could expose that, whatever the perceived past failures in training, the root cause, that the training would have purportedly addressed, remains obscure. Forget worrying about training until the root cause is identified within the system.

In any event, training will seldom be the best way of eliminating a problem. Redesign of the system will always be the first thing to consider.

3. Train managers and new employees

Uncontroversial but I think Deming overstated businesses’ failure to appreciate this.

4. Managers need to understand the company

Uncontroversial but I think Deming overstated businesses’ failure to appreciate this.

5. Managers need to understand variation

So much of Deming’s approach was about rigorous criticism of business data and the diligent separation of signal and noise. Those are topics that certainly have greater salience than a quarter of a century ago. Nate Silver has done much to awaken appetites for statistical thinking and the Six Sigma discipline has alerted the many to the wealth of available tools and techniques. Despite that, I am unpersuaded that genuine statistical literacy and numeracy (both are important) are any more common now than in the days of the first IBM PC.

Deming’s banner headline here is Institute training on the job. I think the point sits uncomfortably. I would have imagined that it is business schools and not employers who should apply their energies to developing and promoting quantitative skills in executives. One of the distractions that has beset industrial statistics is its propensity to create a variety of vernacular approaches with conflicting vocabularies and competing champion priorities: Taguchi methods, Six Sigma, SPC, Shainin, … . The situation is aggravated by the differential enthusiasms between corporations for the individual brands. Even within a single strand such as Six Sigma there is a frustrating variety of nomenclature, content and emphasis.

It’s not training on the job that’s needed. It is the academic industry here that is failing to provide what business needs.

6. Recognise that people learn in different ways

Of this I remain unpersuaded. I do not believe that people learn to drive motor cars in different ways. It can’t be done from theory alone. It can’t be done by writing a song about it. it comes from a subtle interaction of experience and direction. Some people learn without the direction, perhaps because they watch Nelly (see below).

Many have found a resonance between Deming’s point and the Theory of Multiple Intelligences. I fear this has distracted from some of the important themes in business education. As far as I can see, the theory has no real empirical support. Professor John White of the University of London, Institute of Education has firmly debunked the idea (Howard Gardner : the myth of Multiple Intelligences).

7. Don’t rely on watch Nelly

After my academic and vocational training as a lawyer, I followed a senior barrister around for six months, then slightly less closely for another six months. I also went to court and sat behind barristers in their first few years of practice so that I could smell what I would be doing a few months later.

It was important. So was the academic study and so was the classroom vocational training. It comes back to understanding how the training is supposed to achieve its objectives and designing learning from that standpoint.

8. Be inflexible as to work standards

This is tremendously dangerous advice for anybody lacking statistical literacy and numeracy (both).

I will come back to this but it embraces some of my earlier postings on process discipline.

9. Teach customer needs

This is the gem. Employee engagement is a popular concern. Employees who have no sight of how their job impacts the customer, who pays their wages, will soon see the process discipline that is essential to operational excellence as arbitrary and vexatious. Their mindfulness and diligence cannot but be affected by the expectation that they can operate in a cognitive vacuum.

Walter Shewhart famously observed that Data have no meaning apart from their context. By extension, continual re-orientation to the Voice of the Customer gives meaning to structure, process and procedure on the shop floor; it resolves ambiguity as to method in favour of the end-user; it fosters extrinsic, rather than intrinsic, motivation; and it sets the external standard by which conduct and alignment to the business will be judged and governed.

Deconstructing Deming V – Improve constantly and forever

Posted on by
Reply

5. Improve constantly and forever the system of production and service, to improve quality and productivity, and thus constantly decrease costs.

W Edwards Deming Point 5 of Deming’s 14 Points. Surely about this there can be no controversy.

Improvement means reducing operating costs, enhancing customer value, and developing flexibility and agility. Improvement means constantly diminishing the misalignment between the Voice of the Process and the Voice of the Customer.

The UK awaits fresh productivity statistics next month but the figures up to the end of 2013 make sobering reading. UK productivity has been in miserable decline since 2008. In response to tightening of demand, failures of liquidity, absence of safe investment alternatives, rises in taxation and straightened cash flows, the aggregate response of industry has been a decline in human efficiency.

The reasons this has happened are no doubt complex. The paradox remains that it is improvement in productivity that grows sustainable rewards, captures markets and releases working capital for new ventures. At first sight it appears the answer to all the ills of a recession.

How will you know?

In their seminal model for improving productivity, Thomas Nolan and Lloyd Provost posed the question:

How will you know when a change is an improvement?

It is such a simple questions but it is too seldom asked and I suspect that itself is a major barrier to improvement.

We are beset by human induced change, by government and by business managers. The essential discipline is critically to question whether such change results in an improvement. It is an unpopular question. Nobody who champions a particular change wants to be proved wrong, or confronted with a marginal improvement that fails to live up to an extravagant promise.

Business measurement is mandated in the modern corporation. Businesses, governments, organisations abound with KPIs, metrics, “Big Ys”, results measures … and often a distracting argument over what to call them. There is no lack of numbers for answering the question. We are constantly assured that we now have the Big Data whose absence frustrated past strategy.

The habitual analytic tool in old-style businesses was what Don Wheeler mischievously named the executive time series, two numbers, one larger (or smaller) than the other, selected to show movement in the desired direction. That is, as Scottish folklorist Andrew Lang put it:

… using statistics in the same way that a drunk uses lamp-posts — for support rather than illumination.

It is a moral certainty that no two measurements will yield the same number. One will be larger than the other. It will be easy to select two to support any pet project or theory.

Building a persuasive case that improvement has happened firstly requires a rigorously constructed baseline. Without an objective description of the historical experience base, claims as to improvement are simply speculative.

And beyond that, what the executive time series cannot do is distinguish signal from noise. It cannot help because the answer to the question When will you know …? is When there is a signal in the data. That can only be answered with the diligent and rigorous use of process behaviour charts.

At the top of this page is a “RearView” tab. Without the trenchant and determined use of process behaviour charts there is not even a white line in the rear view mirror. The only signal will come from the “bang” when we hit the kerb.

What to improve

Deming’s further message was that it was every process that was to be improved, not simply those whose customer was the end consumer. Many processes have internal customers with their own voice. Processes of management of human resources, maintenance and accounting can all have a critical impact on organisation performance. They must keep on getting better too.

Being held to account is never comfortable but neither is the realisation that we have surrendered control of assets without the means of knowing when such assets are incrementally put to increasingly efficient, effective and agile use.

We need louder demands of “Show me!”

Target and the Targeteers

Posted on by
Reply

This blog appeared on the Royal Statistical Society website Statslife on 29 May 2014

DartboardJohn Pullinger, newly appointed head of the UK Statistics Authority, has given a trenchant warning about the “unsophisticated” use of targets. As reported in The Times (London) (“Targets could be skewing the truth, statistics chief warns”, 26 May 2014 – paywall) he cautions:

Anywhere we have had targets, there is a danger that they become an end in themselves and people lose sight of what they’re trying to achieve. We have numbers everywhere but haven’t been well enough schooled on how to use them and that’s where problems occur.

He goes on.

The whole point of all these things is to change behaviour. The trick is to have a sophisticated understanding of what will happen when you put these things out.

Pullinger makes it clear that he is no opponent of targets, but that in the hands of the unskilled they can create perverse incentives, encouraging behaviour that distorts the system they sought to control and frustrating the very improvement they were implemented to achieve.

For example, two train companies are being assessed by the regulator for punctuality. A train is defined as “on-time” if it arrives within 5 minutes of schedule. The target is 95% punctuality.
TrainTargets
Evidently, simple management by target fails to reveal that Company 1 is doing better than Company 2 in offering a punctual service to its passengers. A simple statement of “95% punctuality (punctuality defined as arriving within 5 minutes of timetable)” discards much of the information in the data.

Further, when presented with a train that has slipped outside the 5 minute tolerance, a manager held solely to the target of 95% has no incentive to stop the late train from slipping even further behind. Certainly, if it puts further trains at risk of lateness, there will always be a temptation to strip it of all priority. Here, the target is not only a barrier to effective measurement and improvement, it is a threat to the proper operation of the railway. That is the point that Pullinger was seeking to make about the behaviour induced by the target.

And again, targets often provide only a “snapshot” rather than the “video” that discloses the information in the data that can be used for planning and managing an enterprise.

I am glad that Pullinger was not hesitant to remind users that proper deployment of system measurement requires an appreciation of psychology. Nobel Laureate psychologist Daniel Kahneman warns of the inherent human trait of thinking that What you see is all there is (WYSIATI). On their own, targets do little to guard against such bounded rationality.

In support of a corporate programme of improvement and integrated in a culture of rigorous data criticism, targets have manifest benefits. They communicate improvement priorities. They build confidence between interfacing processes. They provide constraints and parameters that prevent the system causing harm. Harm to others or harm to itself. What is important is that the targets do not become a shield to weak managers who wish to hide their lack of understanding of their own processes behind the defence that “all targets were met”.

However, all that requires some sophistication in approach. I think the following points provide a basis for auditing how an organisation is using targets.

Risk assessment

Targets should be risk assessed, anticipating realistic psychology and envisaging the range of behaviours the targets are likely to catalyse.

Customer focus

Anyone tasked with operating to a target should be periodically challenged with a review of the Voice of the Customer and how their own role contributes to the organisational system. The target is only an aid to the continual improvement of the alignment between the Voice of the Process and the Voice of the Customer. That is the only game in town.

Borrowed validation

Any organisation of any size will usually have independent data of sufficient borrowing strength to support mutual validation. There was a very good recent example of this in the UK where falling crime statistics, about which the public were rightly cynical and incredulous, were effectively validated by data collection from hospital emergency departments (Violent crime in England and Wales falls again, A&E data shows).

Over-adjustment

Mechanisms must be in place to deter over-adjustment, what W Edwards Deming called “tampering”, where naïve pursuit of a target adds variation and degrades performance.

Discipline

Employees must be left in no doubt that lack of care in maintaining the integrity of the organisational system and pursuing customer excellence will not be excused by mere adherence to a target, no matter how heroic.

Targets are for the guidance of the wise. To regard them as anything else is to ask them to do too much.

Deconstructing Deming IV – Supply chain

Posted on by
Reply

4. End the practice of awarding business on the basis of a price tag. Instead, minimize total cost. Move towards a single supplier for any one item, on a long-term relationship of loyalty and trust.

W Edwards Deming Point 4 of Deming’s 14 Points. For me, this is where Deming’s thinking starts to mark itself out from mainstream thinking. Moreover, the departure is tough to follow.

The key phrase is “long-term relationship of loyalty and trust”. Deming believed that benefit was maximised when organisations co-operated to create customer value and eliminate waste, internally and at the interface.

He bemoaned the “adversarial” nature of western purchasing, criticising it as wasteful and operating counter to continual improvement. Continual improvement is synonymous with improving the alignment between the voice of the process and the voice of the customer.

Deming further raised the more technical statistical issue that inter-supplier variability would always be greater than intra-supplier variability. In that itself, he argued, lay a dominant source of variation, and inevitably cost. Choosing a single supplier eliminated such variation at a stroke.

Trust

I have blogged a lot about trust here. The fact is that the business world turns on trust. This is not an obscure or even novel insight. I have blogged elsewhere about Matt Ridley’s analysis of trust in the evolution of co-operation. In his book The Origins of Virtue he quotes Nobel Laureate economist Kenneth Arrow.

Virtually every commercial transaction has within itself an element of trust.

— and entrepreneur Nigel Vinson:

Trust everyone unless you have a reason not to.

But Deming wanted to go further and end the perpetual challenge as to price tag and the perilously provisional wedlock of business entities. Value was created through a chain, or even network, of activities. Organisational boundaries, and the consequential border skirmishes, were effectively internal disputes, irrelevant to the customer, other than in being antagonistic to his interests.

For Deming, the animus of continual improvement, motivated by the workforce’s “joy in work”, would replace the fear of being under priced, or the greed for tapping “blue ocean” profits, as the prime mover of enterprise. Businesses so driven would naturally co-operate rather than compete and liberate a cascade of escalating economic benefits inherent in common purpose.

Ease

However, I think that the difficulty of such relationships is that human beings soon become conservative and complacent. They will not face the big challenges. Without the fear and the greed, it would be unthinkable to marshal the sort of resources that are necessary to develop a new computer or a novel aero-engine. It would be unthinkable to gamble society’s accumulated wealth on developing a new drug, a technology predicated on the microscopic bases of life or an income stream dependent upon populating outer space.

The principle is akin to Daniel Kahneman’s concept of cognitive ease. Each of us is disinclined to think too hard. Only greed or fear will be the spur, to hard thinking or to risk taking. Businesses represent real risk for their investors. Risks that investors are only willing to take over a finite horizon.

Economics

In commercial law, we often talk about business people dealing at arm’s length. We use that term to emphasise that the relationship is one of calculation as to profit and loss, without an emotional or affective dimension. Ventures between enterprises are not marriages “in sickness and in health”. The extent to which any organisation can be prepared to accommodate the misfortune of another is strictly limited to the self interest of a short time scale. To go further is to mistake inter-organisational dynamics for inter-personal affection.

Organisations only form, express and develop their relationships through the individuals who work for them. Inevitable misalignments arise and create agency costs. People shift, though Deming wished they didn’t. It is very difficult to recognise the sort of co-habitation that Deming envisaged in law. And if not recognised in law, how can the trust operate long term over shifting agents? The English case of Baird Textile Holdings v M&S illustrates the difficulties of trying to found business expectations on past relationships.

What Deming seems to ignore is the wealth of economic scholarship that is relevant to supply chain decisions. He identifies limitations of the competitive environment and exhorts us to embrace the benefits of closer and longer lasting ties. However, nowhere does he treat the advantages of remorseless competition or the disadvantages of a too narrow supply base.

In Deming’s analysis there is no concept of an efficient breach, as the costs (to society) of the destruction of trust are deemed to be, at once, unknown and unknowable, but surely to outweigh the calculations of the profit and loss account.

Competition law

There seems little doubt that much of what Deming advocated as to co-operation between organisations, and in particular in sharing information, would run foul of modern competition law. Deming saw competition law as a barrier to his new philosophy. In Out of the Crisis he wrote (p26):

Obstacles to the competitive position of American industry created by government regulations and anti-trust activities must be revised to support the well-being of the American people, and not to depress it.

The history of economic development offers ample testimony as to what happens when business people combine against the public, free from supervision or sanction. Much as Deming believed his exhortations would benefit the public, those sort of economic-legal policies can only be assessed through data generation on a global scale, trenchant analysis and imaginative policy creation. Then more data generation …. A point that one would have hoped that Deming would appreciate.

Legacy

Nominating a single supplier, embraced in a long term relationship of tolerance, mutual understanding and (lawful) benefit sharing, without a lucid vision of how that relationship would be managed and a cogent analysis of the risks, mitigated with robust safeguards, would be folly indeed.

However, Deming does remind us of some fundamentals of doing business successfully.

Build trust.

Work together.

Continually seek to reduce variation.

The future of p-values

Posted on by
Reply

Another attack on p-values. This time by Regina Nuzzo in prestigious science journal Nature. Nuzzo advances the usual criticisms clearly and trenchantly. I hope that this will start to make people think hard about using probability to make decisions.

However, for me, the analysis still does not go deep enough. US baseball commentator Yogi Berra is reputed once to have observed that:

It’s tough to make predictions, especially about the future.

The fact that scientists work with confidence intervals, whereas if society is interested in such things it is interested in prediction intervals, belies the proper recognition of the future in much scientific writing.

The principal reason for doing statistics is to improve the reliability of predictions and forecasts. But the foundational question is whether the past is even representative of the future. Unless the past is representative of the future then it is of no assistance in forecasting. Many statisticians have emphasised the important property that any process must display to allow even tentative predictions about its future behaviour. Johnson and de Finetti called the property exchangeability, Shewhart and Deming called it statistical control, Don Wheeler coined the more suggestive term stable and predictable.

Shewhart once observed:

Both pure and applied science have gradually pushed further and further the requirements for accuracy and precision. However, applied science, particularly in the mass production of interchangeable parts, is even more exacting than pure science in certain matters of accuracy and precision.

Perhaps its unsurprising then that the concept is more widely relied upon in business than in scientific writing. All the same, statistical analysis begins and ends with considerations of stability. An analysis in which p-values do not assist.

At the head of this page is a tab labelled “Rearview” where I have surveyed the matter more widely. I would like to think of this as supplementary to Nuzzo’s views.